{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "import numpy as np\n",
    "import cv2\n",
    "from os.path import join\n",
    "import os\n",
    "import random\n",
    "from functools import partial"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "from keras.models import Model, load_model\n",
    "from keras.layers import Input, Conv2D, MaxPooling2D, UpSampling2D, Reshape, concatenate\n",
    "from keras.optimizers import Adam\n",
    "from keras.layers.advanced_activations import ELU\n",
    "from keras.layers.normalization import BatchNormalization\n",
    "from keras import backend as K\n",
    "\n",
    "import tensorflow as tf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "channels_last\n"
     ]
    }
   ],
   "source": [
    "K.set_image_dim_ordering('tf')\n",
    "print(K.image_data_format())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def get_unet(size, n_cls):\n",
    "    inputs = Input((size, size, 3))\n",
    "    \n",
    "    conv1 = BatchNormalization()(inputs)\n",
    "    conv1 = Conv2D(32, (3, 3), padding='same')(conv1)\n",
    "    conv1 = BatchNormalization()(conv1)\n",
    "    conv1 = ELU()(conv1)\n",
    "    conv1 = Conv2D(32, (3, 3), padding='same')(conv1)\n",
    "    conv1 = BatchNormalization()(conv1)\n",
    "    conv1 = ELU()(conv1)\n",
    "    pool1 = MaxPooling2D(pool_size=(2, 2))(conv1)\n",
    "\n",
    "    conv2 = Conv2D(64, (3, 3), padding='same')(pool1)\n",
    "    conv2 = BatchNormalization()(conv2)\n",
    "    conv2 = ELU()(conv2)\n",
    "    conv2 = Conv2D(64, (3, 3), padding='same')(conv2)\n",
    "    conv2 = BatchNormalization()(conv2)\n",
    "    conv2 = ELU()(conv2)\n",
    "    pool2 = MaxPooling2D(pool_size=(2, 2))(conv2)\n",
    "\n",
    "    conv3 = Conv2D(128, (3, 3), padding='same')(pool2)\n",
    "    conv3 = BatchNormalization()(conv3)\n",
    "    conv3 = ELU()(conv3)\n",
    "    conv3 = Conv2D(128, (3, 3), padding='same')(conv3)\n",
    "    conv3 = BatchNormalization()(conv3)\n",
    "    conv3 = ELU()(conv3)\n",
    "    pool3 = MaxPooling2D(pool_size=(2, 2))(conv3)\n",
    "\n",
    "    conv4 = Conv2D(256, (3, 3), padding='same')(pool3)\n",
    "    conv4 = BatchNormalization()(conv4)\n",
    "    conv4 = ELU()(conv4)\n",
    "    conv4 = Conv2D(256, (3, 3), padding='same')(conv4)\n",
    "    conv4 = BatchNormalization()(conv4)\n",
    "    conv4 = ELU()(conv4)\n",
    "    \n",
    "    pool4 = MaxPooling2D(pool_size=(2, 2))(conv4)\n",
    "\n",
    "    conv5 = Conv2D(512, (3, 3), padding='same')(pool4)\n",
    "    conv5 = BatchNormalization()(conv5)\n",
    "    conv5 = ELU()(conv5)\n",
    "    conv5 = Conv2D(512, (3, 3), padding='same')(conv5)\n",
    "    conv5 = BatchNormalization()(conv5)\n",
    "    conv5 = ELU()(conv5)\n",
    "\n",
    "    up6 = concatenate([UpSampling2D(size=(2, 2))(conv5), conv4], axis=3)\n",
    "    conv6 = Conv2D(256, (3, 3), padding='same')(up6)\n",
    "    conv6 = BatchNormalization()(conv6)\n",
    "    conv6 = ELU()(conv6)\n",
    "    conv6 = Conv2D(256, (3, 3), padding='same')(conv6)\n",
    "    conv6 = BatchNormalization()(conv6)\n",
    "    conv6 = ELU()(conv6)\n",
    "\n",
    "    up7 = concatenate([UpSampling2D(size=(2, 2))(conv6), conv3], axis=3)\n",
    "    conv7 = Conv2D(128, (3, 3), padding='same')(up7)\n",
    "    conv7 = BatchNormalization()(conv7)\n",
    "    conv7 = ELU()(conv7)\n",
    "    conv7 = Conv2D(128, (3, 3), padding='same')(conv7)\n",
    "    conv7 = BatchNormalization()(conv7)\n",
    "    conv7 = ELU()(conv7)\n",
    "\n",
    "    up8 = concatenate([UpSampling2D(size=(2, 2))(conv7), conv2], axis=3)\n",
    "    conv8 = Conv2D(64, (3, 3), padding='same')(up8)\n",
    "    conv8 = BatchNormalization()(conv8)\n",
    "    conv8 = ELU()(conv8)\n",
    "    conv8 = Conv2D(64, (3, 3), padding='same')(conv8)\n",
    "    conv8 = BatchNormalization()(conv8)\n",
    "    conv8 = ELU()(conv8)\n",
    "\n",
    "    up9 = concatenate([UpSampling2D(size=(2, 2))(conv8), conv1], axis=3)\n",
    "    conv9 = Conv2D(32, (3, 3), padding='same')(up9)\n",
    "    conv9 = BatchNormalization()(conv9)\n",
    "    conv9 = ELU()(conv9)\n",
    "    conv9 = Conv2D(32, (3, 3), padding='same')(conv9)\n",
    "    conv9 = BatchNormalization()(conv9)\n",
    "    conv9 = ELU()(conv9)\n",
    "\n",
    "    conv10 = Conv2D(n_cls, (1, 1), activation='softmax')(conv9)\n",
    "\n",
    "    model = Model(inputs=inputs, outputs=conv10)\n",
    "    return model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "class BatchGenerator:\n",
    "\n",
    "    @staticmethod\n",
    "    def to_one_hot(img, n_cls):\n",
    "        return (np.arange(n_cls) == img[:, :, None]).astype(int)\n",
    "    \n",
    "    def __init__(self, txt_filepath, size, n_cls, batch_size):\n",
    "        self.lines = []\n",
    "        for line in open(txt_filepath, 'r').readlines():\n",
    "            line = line.strip()\n",
    "            if len(line) > 0:\n",
    "                self.lines.append(line)\n",
    "        self.size = size\n",
    "        self.n_cls = n_cls\n",
    "        self.batch_size = batch_size\n",
    "        self.i = 0\n",
    "    \n",
    "    def get_sample(self):\n",
    "        if self.i == 0:\n",
    "            random.shuffle(self.lines)\n",
    "        orig_filepath, gt_filepath = self.lines[self.i].split()\n",
    "        orig = cv2.imread(orig_filepath) # 1 and 3 channels swapped\n",
    "        orig = cv2.resize(orig, (size, size))\n",
    "        gt = cv2.imread(gt_filepath)[:, :, 0]\n",
    "        gt = cv2.resize(gt, (self.size, self.size), cv2.INTER_NEAREST)\n",
    "        gt = BatchGenerator.to_one_hot(gt, self.n_cls + 1) #  + neutral class\n",
    "        self.i = (self.i + 1) % len(self.lines)\n",
    "        return orig, gt\n",
    "    \n",
    "    def get_batch(self):\n",
    "        while True:\n",
    "            orig_batch = np.zeros((self.batch_size, self.size, self.size, 3))\n",
    "            gt_batch = np.zeros((self.batch_size, self.size, self.size, self.n_cls + 1))\n",
    "            for i in range(self.batch_size):\n",
    "                orig, gt = self.get_sample()\n",
    "                orig_batch[i] = orig\n",
    "                gt_batch[i] = gt\n",
    "            yield orig_batch, gt_batch\n",
    "            \n",
    "    def get_size(self):\n",
    "        return len(self.lines)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "data_dirpath = '/data'\n",
    "size = 224\n",
    "n_cls = 3\n",
    "batch_size = 8\n",
    "train_batch_generator = BatchGenerator(join(data_dirpath, 'train.txt'), size, n_cls, batch_size)\n",
    "val_batch_generator = BatchGenerator(join(data_dirpath, 'val.txt'), size, n_cls, batch_size)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from keras.backend.tensorflow_backend import _to_tensor\n",
    "from keras.backend.common import _EPSILON\n",
    "\n",
    "def my_bce(target, output):\n",
    "    epsilon = _to_tensor(_EPSILON, output.dtype.base_dtype)\n",
    "    output = tf.clip_by_value(output, epsilon, 1. - epsilon)\n",
    "    \n",
    "    return -tf.reduce_sum(target[:, :, :, :-1] * tf.log(output),\n",
    "                           axis=-1)\n",
    "\n",
    "def my_acc(target, output):\n",
    "    target = K.cast(target, tf.int32)\n",
    "    correct_count = K.sum(K.cast(K.equal(K.cast(K.argmax(target, axis=-1), tf.int32), \n",
    "                                         K.cast(K.argmax(output, axis=-1), tf.int32)), tf.int32))\n",
    "    neutral_count = K.sum(K.cast(K.equal(target[:, :, :, -1], K.variable(1, dtype=tf.int32)), tf.int32))\n",
    "    total_count = K.prod(K.shape(output)[:-1]) - neutral_count\n",
    "    return tf.cast(correct_count / total_count, tf.float32)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "model = get_unet(size, n_cls)\n",
    "model.compile(optimizer=Adam(lr=0.01), loss=my_bce, metrics=[my_acc])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/5\n",
      "20/20 [==============================] - 11s - loss: 0.6351 - my_acc: 0.7517 - val_loss: 6.3580 - val_my_acc: 0.5212\n",
      "Epoch 2/5\n",
      "20/20 [==============================] - 9s - loss: 0.3504 - my_acc: 0.8530 - val_loss: 6.3024 - val_my_acc: 0.5230\n",
      "Epoch 3/5\n",
      "20/20 [==============================] - 9s - loss: 0.2765 - my_acc: 0.8757 - val_loss: 5.9011 - val_my_acc: 0.4270\n",
      "Epoch 4/5\n",
      "20/20 [==============================] - 9s - loss: 0.2755 - my_acc: 0.8785 - val_loss: 3.6580 - val_my_acc: 0.5455\n",
      "Epoch 5/5\n",
      "20/20 [==============================] - 9s - loss: 0.2556 - my_acc: 0.8871 - val_loss: 4.3985 - val_my_acc: 0.5316\n"
     ]
    }
   ],
   "source": [
    "history = model.fit_generator(train_batch_generator.get_batch(), \n",
    "                              steps_per_epoch=train_batch_generator.get_size() // batch_size,\n",
    "                              epochs=5,\n",
    "                              validation_data=val_batch_generator.get_batch(),\n",
    "                              validation_steps=val_batch_generator.get_size() // batch_size)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "model_filepath = 'best.h5'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "model.save(model_filepath)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "model = load_model(model_filepath, custom_objects={'my_acc': my_acc, 'my_bce': my_bce})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Acc: 0.471\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f727416fb00>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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EjVYDadkopYiTLvXtLcrHD9Lrtbj5ta/n5DNfIeW6lHMHafcFxWoez7Uoz0wgxF5H/vfH\niyKiUQmJMgmx0aANPT8mihKIu7Q6TdpBjyAa4kcRxgiicEjk+wgMGI1lwHItjIlAG+YO7MNKpYjC\nmChJSBLBQBukFii1YysiuUzZNQ+ev5vnCjw79732fGYnz14WsZfuj4Rb2TCInD1pexUNXDYF9rb1\nfIflrkLaqzR83vP+X6PVa5PILGfOPIyJI5pBBL2Id7/21TS6bWoNzdzUPMZYhINV6kuXML1ttqMB\nT2+2eXztArVln0nSyHqKfKrC/EyFfccPcuHCWVY213ny0iaVyiE2VjaxMzDobyBL04hUhG1rXnXb\nS0lVMug4ZrDVw8kW6XU79PtNXGVRtjKsXVrkbSduRnfaDDsB2ayiV++QdhyEn/CSQ/uYm9qPtMqk\ng5B2kFAYr5BN5cmn0tz9wAO8/1d/jktff5R8VpIujHP2iUfYt38/AOnsHIHVoXJgP6pnUYtt1r59\nksUnn2JteYNTF07Tjwc0toe4Y1Va68uMF2d5+eE56muKffP7gJBu7UnKqTQSC0nCvtI4cSSxjcOR\nO47DRIZUIUOn28crprGKaYZrDcJBj5UnTxP0IxyZYvXSI2TGxjES+u0h7U6XdEphK4nlWvRqNYxO\niJOYRBssyybsDfC80U6D5SgMMTrR6DAeKSM/IF8Zx3ZsTBTjHJ4nikJMFBLrhFvf8noYk0zN7afT\nXUQ5DhKNNIKx+RmQEpUbQ5jns9K/Gy8KpSCSBG0gCmK63T79Xo8ojhh2+ySEBMOQMIgJwwSkQOuY\nQRQTJAZfx/h6NJBBZJDGkMkpTBIhpAat8WxFzrURaGQSgk6I99j8X7z3kzxy/yIfuOejQMBzdxf2\n7hxEQBpo8FzFsNcXoLG9Aa6115m4i10B3217tyxcVhy7+fayiZFzcmi26W/3MZbNUAf06nWmJgt8\n4F/8FO98x2t56c0HmSyWGZ+oEHa3SPpt1s5dRMgUQib0Gh2McVlsdwldGI4VOTSb5Qvf/CbXXHOc\nBx6+wJGrDrF/YgrHdrj/6/cRNAck3RgTCiwp8DI5broqxcnaJtEwIQ6HRN0uKcegScgVqzhKc+O1\nB1lcXOeB8w/iehax1Kxfuoib0bSbbbSdsNTukXKG3HAkz1ZniAoDSnMFkkTTaTSZnj3GuXWHxxaW\nWFm+RHkszVK9w4WVc4zYW5GffM276DTr+IMOXhKRv2qeyakpnnriIbxUgWHGg1aT3nYLrzBNM+xz\nprdNKl/ijlsPAw6iXMVJ7QdgrFRiYXWdmapHZiZPgkP56EG82cMkXR+pbKJ6F69UJIgE2rbJzo2z\n1qwhnEmCTgPpOdSWllHCYtiJQI+2HHWUgLIxcYLruvhBhJ126QcRUkI0jECDEAKhFGiD0YbyeJlE\na3QxixV2UQKEkGQm8pw++Q1KRw8gcw6xTsCzMDJL0G8RxgPSeRc6HbTayzq/P14USsEWAm0Apem2\nO9SaTZqDNh0/oOt3CYI+3U6XYDhiB9oY+t0BfhTiD32GwwFBHBJEPkZIYj1yzESRwrIcpJIIpTDC\nBSExykIKj10hzUsP185QvDTke23/XQ2r99xL6GeFeq+gK0ASKUGY7PUL7N2O3K3j+UO/VwnsKpmE\nkfIIAcPXPvcFdNikO+jRq9XJFBRdqfng7/8RX/vmST7xubu57Y4j1GobNNptBmGAk84S64CmVpTG\nZ0APMN0eA7/NmcUlNjc3McEWJ08+zY++9jWEQZ8DV8/Tr28hHYmIu7Q2l4gcQb8T4vdinqz16F7q\nkPMKGBPjOIb185dQjkS6io3VBe655z6yaYelpSHX3nY7dhKSL+8jGGiGrT4Lj53Ccy3CMOaZ9Yjq\n9CyukyWoJ3SXl8iIBN3rU+t2QBsOVqZ58tIKRyr7yUcWIwYHVdfgKYvxfJowtujKMvc+8hT5whSl\n8SLV/DzlA9ewf3qSa6sT5DIG1y6h3C7OcORS++93fhRIY3SN8ekKYSxZq/VxUynajQETYzmGjYvY\nlRJe3iMMYoa9AC/t4GVsok6bYK1JOhUTx2b0a1tQOXCAUAiiOCFfnUKkPNAxQoLf65NKK4RyQcIw\nSNAI4jAmiROMMeg4RLkO3WgJHWmOvvZ6OpcaSHs0l3rrDTy3zNbTNR7+5Bc5dWaT0mQVHTcQVgYM\npKdKJDqhcOQALxT/w+IU9iKSI+F57KEnsewEnQBRgqUUMWbknUUilBytzwLqtQ6tVodOr4enLFQm\nTeyHVMdLLGxEHJgQKKmRWIRRhBQaY/IkThpMiyQO2RXC21/xem6NhghsRkwg5rJA7+4c7N0FSJAM\nGAnrboDSrqBHeG6K6FklshvfsJdZ7Na5d+tzL6u4nL/XP8uHP/F5fuF9P4vIT5AEhqDRYducY/9t\nP0Qcd7mwtcUzK9v8xI+8Ct2pcdu1x3j8yUdRQuLYGcZmqqSyORIdEscRCIUnPZAuK+0uN5fmmN43\ngcy4JLZFyarQ0iGZcEgmux8hQqQfkdiKiYk89dYWyhmwvnSW/KEZ2usdpBUTS8lguM3c9FGWTj9O\naAz5yBCbdYQ25PNjbJ0/jW07REFEY7OGsXKU5SW2V1uUq3lcL08z3Kay7wC1Zo1QJew7XGG7ocil\nFE+dvZvZqePPjtTNb3oH4hN3ccOxa3lqqU5KLGJLzXve9jruP7tAcaqIpQW5Y3N4sSTsrrO5uoEx\nAs9yiKJnaLdGPiMhK5x64gJuxmXmJfvprV2iet3LqG3UiOwyuWlBzpP4gxCtNYNWH7/Vp1gpIgtz\nqF6A61ko2yY7OUmjXkMEMUkSknFS9IOQMIgQwkYKSGJIj2UY9GI0EcqzQSmEH6BcRaQNSkK/nWBP\nlzn9ye9idEymnGHYSkiVXcKoQzpVoFu7SMYOubgekfYUg2EP1ZHYR+bx8n0mDs+xePfDvBC8KJSC\njmMUBmVJksgQtgYEwWglFhi0BiFASIlJRgKztbyJkoKthS20EQgJQgqu2n+IxW98nWv+yY/sWP8h\nKdel2WkRUyQOBwhp0MLh8nZgCsv2uCycFoZ4xwG5u9LvMoKY+566ky98+CTe2Bivf9vV3H7duxnt\nNAjAJp3OI6O9TAK+d8tzV4ns9S98byBUq+XTq/f50rfu4cSN1xLUG1x/y+2QT/P4/Q9SLivirkMS\nDPnQpz7D1dfdxjU5H+FYuNIhDCWZQgUZt/CdFLIjiUVIICKEAs9Lc/srb+LMmRXGteJXPvUR/uPb\nX0+5UCbCIQjaINPEdLjm4H7O1bdG5lfXIFMucbNDKZUmDJr0A40UMRtrF6hMVNlcXcazPaJBGi/X\no9Vew3MzaNPExIpEaNKex/LCClGnzeSYZOPcA+TnDrK5uUhqbB+Dep/lWFKZq7K22sGTeXR82fEr\nRIE3v+YNDFyb5pPnOPXUAMuWzE8otqNpaG3gVKZYWDpJxpsgX07R6XbZv3+aTsHjvi9+kVuuu/5y\nfTogdlJ0u22OH7uJpV4HK51hYiYg3m6yvjhA6oSg1SddKpD4Ppn5Sdz0NGuPP0LQG5ItaxoryyRB\nQqacpb1WI4wEluUSRgm2ZRNrSHyfnt9DBBFIhUYg9CgmQRuN5dgYDFEgKc+V2dhsIqVFOBySn9tP\nf2OZeL1J2N0AKUh5PqY9xPcV9lgaS6Xo1OroMGDjmy9MIcCLxHxIpMQYiZIO0mgs1wIxCmNOEAhG\nlExoje1YaDGKetSJITYGYfRIWRjB4sJ51s9uI5VCSInWalRax9huDpH4OzEEe2n9Xht+5Eu4rBD2\nCnPCp5++i0994ixdMqxsdbjn0UW+evGTjHwRBohJTIzruXvKwXPDmPcKvnpenl0fQkxt8Az5Yp7F\n5WWSXpe7PvcZfunf/nsWTz3M+rnHueaG6xCRJOj1sFMevbrPmTOPc9d9X2F8qkrKc7j2ujkG3QY9\nPyAJE9r1FSzpIKwcfr9Ntx9yMQgp5rJ87czXSV1c48N//WHuuOkm8uMehfIMM0eu4sD89bhpBzm0\ncBJJu9ums7lBr7bM2FU5pg+Mo3SI9kfsK4gSlJth2GkxiDsM2n2aiysEQRfLKbDv8CG8zCSebSOH\nMePTZdbPLtJ386zV1sk4OVqbS0xddZBOa5PGao1MrkAqBVPZSRLWn50/119/mDBqM18cY63dIisE\nt77i7QjXYaGxxulHHyHv5zh/ZoOFpZCh8ug5eWoba8ReQjM8x7OBY1qgu0O6G0MeOHcO4dqUsx6O\nnSOIXVK5PAkjAc7v34+xXLYXl0jbkJs5ipOyGTRDLKGRScKg1wMjWas1UCmN4znoOMaEIam0S8oW\nGEvhpu1RuJplgZIkQYJJYmzPJun51M9fGoXwa0001BRKebKVApZWKCkgGpkuuWoOHRgyWY8wCLHE\nEOF4xPqFH3x8USgFT1kYo5GWjbAVQlmkXJtUysF1bSzHRlkKYUlQ4HkWjmVjuzaubYGjEI6FkbBw\nYYXt+gJaMvIfJCCdHI6ysVMS6eQBveONfb6gPv/8Ac/7vs2Dn36KyalJrj92gGPHj2A1DJfORHvy\nKCZK+7Clw66P4bkxDXvr37slKfd8ZxHqFSrpozg64cbbbiEWkJVp/vKzH0ZNzPDK66+ns7HKoNFH\nCoMOQzLFNH5zSC/ywEox8Hv0Q590yqPfaxN22hSrFVRuHN/vge2RTjl89+GHmZ2f4403vo7EtfnK\ng6tMlGcI6kPGsqDjNuv9Fc7XFggI6Tc6pDJp8tkCoS8YrAwp2EWSMKJ8cBaCAY3NZcLBAMv1mD2q\nKM5VicIQKW0GfZ+17RpZqfHDgJRns7nR48SrXokVt3G0JrE8TOwziAYQe+THMsyWysRxwOJwg298\n7UvP/jrHDh/BCtMcOX6MirZ53SteCygOFSTf+sYCm77FExcWsF3F8uIZsq7FYHGDL3/52yyeqfOt\nRzcYMT3IpXPESUxnYYt8Ks9wfZ3BcIBlYir7ChjbIlew8PIenX6dzMwUpauOc+bUd/CsBIwhCg06\n1hghyGbyYDSyF6IyVUS5gJKjBSdU0Ov42LaNMaBjTRzEJGGEdCyEtEmX0ijLQscGHUdgNHYmTWNp\ngVQmg5Eao5NR+TDGCEN6+ioG3ZjSxBy6C6VjBynf/rIXLI8vCqUQx9EoHDMM8Lw0yrFBypHJIEBI\nsKRACIn1rFNSIJVEKYVnWXiOwrUtbCdNEPQJtEAqC8uxsJVGS0NsCbBshJCEUgGKJKlzmfrDZb/B\n3qjCUfpf3X8vTrFCNwm57rabueHYfpRl2HjiHF/82kfY9Qskic+ttxzhuUzj+T6KvYwBLvsUDAnb\nOHIW0AwI+PzJ+7m0ssQf/82dxNstKmXDxz79WdJCoMMI20mBgCSIGKuOkfU0nrB5z1t+mG7gMwxC\nSrlJMmN5lO3QbaxgAo2XKhBGAWsbW/zl577BoyvPUI4taivbdP1LZOyE2A+pbzaoTh8gTZruwiKd\nVg0nGVJfXsSVIGWCViWiQGN1+3SGCWEi0CagOlNi4UlJELooKYiMwLItHOHS7g3obF3g0C23MD6d\n58Evf5uMVcRTOcLOReqrdZJmQCXvsF1rs7K6SBRJCoVxHl5eZRRlCheeeYqZeYd8zuEtr7mGV7/l\nDVxYXuQ//cmfo9lC1LewCkX6ScR4IY/WAYevPkqYGIrTVQ5OV7iw9HnAkJ/NULn6CKmJEuGwR2Xf\nAVxtsd3ucGlhDTvr0NsecvVr7iBrFNWDc0yWM5Ty8wwaNZRto2wLAczPl2nVGwhHIYzhyNX7+Omf\n+edgEuyUS+KHiCAmDmPwXCzXxiQx0rLIlTJYrsTf7uCVMiglycxMYaRF5PfpbndobdRxPAW2hZXL\nIgSkCkXcaYux6Qq2GxF3hrj+kMHChRcsjy8KpSClAiNRliIKQkbOVYMW7BgP4vJJASFRSoDRGGFA\njk5HgkEgELthoYkcKRZlg1BobRDaMFndj0lgZmYa8FBqjlG8grdzd3au3bRdii+pDFO89GiJn3zH\nWzg0M8+NN7yE3P7DiLxBjR0BuoBkbHya5dU2e89DXK5nN/4ALm977kKDGaAoUh8+DQT8bx/8Q+Ja\ng7/5+jew82NYqQJPP3gOG4fV7TrSzRCQ4Ps+BsGw1yUWip7f55Gz946oqkpjdEy/22B7s4WtBemx\nKsNOm0GFYqlrAAAgAElEQVQ4ZCx/NeWSy3YnJrALxMMOX7vvKbpa4mfL5KtV6ut1EpWgIx/lpnFS\nGcanJhj6MeMzExy55jC249Ec9lGBTzmfJ50psrXVZWrfLKWiB9Iml0uRCMl0dZqgH5PJTrJ6aRkV\nxqixEqvrmzQ6PTqtEM9JaLY2WWsOqJQmqMwexPMmyLkCaxvuffKrLG48hTM5i5cukSpOUFcOAs1f\nfOJDtJaalMfnWFhcZ2VtjXCg2F6v040Mi0tnWTh7gaWnz2BZHhcaCTCgvTlg+6mzTN1wgPalDaIw\nZCgMM/tnyHsF9FYTqUAlAYVSlWjQx81UKM+PMzEzg5Py0LEPiWDp4ga21EgM0rKQbsDrbj+EUhKT\nJFhiZIakCh4yDEl0jEy5KMcmCsLRDlosEEaCBLeax0ornJlxXM8hSTS9WpfZwweYOD6H1gIdGzIm\nYbjdpr60geV5hEGLmSPTL1geXxSORiNAoEmiCGElBINoxArQJDt0QQiNSQTKGLRkJ7TZgKV2NhEE\nCHAcC4PAiAg/0qNAkCRGBxHSGG644708/cR3CKy9pxR3MRLQjl4nL3fPc7nPfvvW1779OWUSDO97\na5VO5/UsrV4AKkBMYE1RLKzsvh3PDV56fhj18yInRQbDBqvrLQoHOphGTMZNEQGtzpDc5AylqSnC\n3pCx8TLbSxtMTs+xtlpDGgu/M8RWgo7WLBmF7WUZ9hrESUwsYmwzoNvoolIumhAZClrxKnID6Dd4\n6NEn8EoFGtsdKhMlJryYpWabqOWz2WojM3lEooksj8KhEvbFizx16jyXzj9DZrZKb3GZBE29XWdq\ndp5+OGTSsjCVPJZlEQ0CjIxZWT7LgetegnQEgR9j+gleysVOxTR1RDZxWF9YIludQRlYbdTI2y2c\nfpEt3+PdP/Um8rkcpy/VufPuL7B86Qx3HL+Kq2b3c+Id/5TbZqYYq8wz6MZU903S7cZceup+JrL7\niLo9Dr3snfzUW97Fb/zmr7CwscLPvevH+fz999BrNUbRtcOE2ZccYXO7jdvtk8yUqB6eZ+HhJ3FL\nYwyjhO21dar7p9DBkGFngBn2CCONjgyDTgvlpIligedYGFcwbEje97M/TxxEaKMQto3ljA7PGZ1g\nEjBKIxLwXBcxM0/3zCV8P0AWx/CSDMNMmn0vOcr5zz9CHASI2LC+vgZ5b+SUtyUi5xEsRmiRoGPN\nYH3AWv/sC5bHFwVTiKIIpSTZ8Sp2ukS2NI6XLmB7OZSbwnNdpLSQlkWsFHIUvUuiQRuDMRr07gkx\nSaITWv2Qfi8gCGPiKEGZmERqxgr7OPDmH0frvdR+Lwx3ffi736e3e05DIvBEiolClZuPv3wn1aKj\nE37mjW9+tr7nlt01G/b6EHaZQxoYInD4zBfv5yOf/DjVnEe1MEGhUCA/UUTpiPL0BIqEzfUNwkGX\n1cU1MpYi7PVxUjZObnTWPgQ6zTrZQoZI9wmMYWDS5MsHqa+sU/KKJGEfGUcEysN3x+gMQoLWECuJ\n2K41OX12ge5am616k0azjtIxk3PTbF5YZPHxM2gy3HDD9ZRdj9a5c4RRAoHGigyDXpv9U7MM/T6d\nQZsbX3EbTs5GJgovW6LWbJEkAXbeYigTJnMeSWIhVjdZu7iAbWcoKBelNQKFGwQ4+QHHD8zzN5/5\nEo43xlWzM5y5/9uY9jbf/PqD/PEff4ZbqvsZOiU21+u4yiPajrAGPmOV4+jcGOOlYxyaS1NNZ4iF\nJiccfuWv/pCPfelviWKDm1ZEkU+/F5ApZLHzRYJel61anamD87iWRXu7h+MIuh2fMIixTIZUeRzj\nOFjZFCpTxHNdLCUJtcFyFKcef4wpNY+VSiOEIhmEOBkPE0ZIywE5CmFWEvo9Q7K9Ra7ooUyCVAGd\nlYu4GcNTX3iUJAqwPAtjKfTQR2wHpKs5ijkP6SowmiTSGBHS6w7ptveG6n9/vCiYgmUppFS87R1v\nQGuJMT5JJDAk+P6ApOfT94foJObuz3yVKJJIbZian2Pm9lsx3RY6DAjq22x02qANSRIQI3CQ+EHA\n0Ngk4Uj4br3xfayf/DBtf40b9r+OTrKBrYok+IQMudTu870s4oXjjv037jztspHd513sVQR9IMfu\nzsX5lUf5zuOneHzxHKfXc8iJNEv3PES+nEMnmliGQIDEQvQ7KDtN1GwxzOXJlLJsrDcopNvkxipk\nUnk26quYKIakQC5t0+yuEw7WEUawubZAarzAxuoqjikwO/8yykcOs3nqKaZmpli8uEwz0Yg4JhgE\n6CDAPjCOX8iSyxYYdGvMHpvhsQcf5J2veRtPX/gk0g4xKJxMjuz4FAtrG2QzeYSXIrIUY6U8zW4d\nFfrMlo+iPUk4jEmcFG4hixUlBL0lQOIV0jS6bSozE9gZh63VdVJpw71PP05hMODkPR/k3T/8m6S0\ngAg6nYBDsxnW1s9hdEDaS5EIl43lJ3n3O9/LZ7/yReJiEc9v0Dyf5uv5l5LNWJxqBVS3tuj5hrlX\nXU84COksb6JcSSXUbHU3SKsc5ckcg1YLL+8SDwP6JMyMjbHR2GR2copw2KZUyLGlBG63R7vto4xA\nRyF+TqMbCa2sz6HrT3DukZPoRON3h6TSDkEU46QM2nKI+x1UWjJo9DF+SOGG43QvLpIeKzDYrJG2\nJGEkEK6F69pEnS5uWeJlUrRrLbJjWWRxEm+wSWVynuVzCxBGvFC8KJiCMYDRLJ19jF59i/52GxMO\nIIgZNAJagyGenUFYWaQ1MhOEhLHxMrcdnuHm41dx683X84q3vIW3vfkNIASfuPNe2o02q5sNVjYb\nBL4mFikakSEPVPMz3PmfPwRIVrdO8+AD5/j5n/4R0hRQzQUSDL/6i++kZQbc8W/+Fb/98T/jnf/8\npfzpn/3eP+DNds9SwPf6EXb/yyHDrulw90MfYGJqnofO30u8PaC3WcdfbnLzS25E2YbKzASuB9sb\nNYJBiyC26Nbr+NrGLhWwPI/JShXl5JGOxdCPyacLJKFPKEOWnn4U17bpRhbpagG7kOLi42fJuznC\nVofWVoNhu0nUj1lvDolJMzamqEyUkUaDFCS9OllcKgdmqRy5ikdOPc2xW2/iU1//FEkwIBxosmmP\nUMc0N1YJez1QPtsXn6RXW6U6dYj9B6dR6Sx+b4PNhXNYcchsdYpua8D0WIrq4X1UTxxk8vgRqqUK\nvTiht7zKsBeTLZTpL67iZmCjm+P0ynl+7E1vZxAGVPdVGMgUSahpx4rqXBFtemTGJrn73i9gp4rc\neM0JDhx6Gad7eb7+1TtB2cxmMkSWjfEHXPj2KTYfucCwOSA/Mc3CqQvkqlVykwXiKMLKTCFkHouI\nqeosaddQLU+wtrhMNOyjXcUN1x0bRZNKMIkmXUojBw5JFBMHHS49/SiCBCuTRmjDoBOgjKE4U8ZC\nIdMZwmGECTWFiQoHrznK1DVXEQYddCSIuoMRE2j7jE2XyUwUGZucxnKyuF6K7pMLiO4GdsbBj7uk\nx4ukS6kXPGtfFEwh0QkaCJo+G52LPHbqFMEgIUgSHCkR0kZahmw2TRxqpBiJURRFPPCd+xn4Q9KO\nQ65cxbItMJpLz5xm5dgUUdQl8BNCA7bj0BjEZAs2iT8AMxJQT/i85MQ1/Nc//jQeFuXxMgrBtx5f\n5RcZkj/zOP/yNz/IE599mPrymX/Am4WMfAh7dxsMI4dknsssQrNef5KP3bXO6Usf4dzjHRINrhYk\ngcPy1jL+MKax3YFeF+MHI8pqWeh0CsvbcQCmXUg5GDtmuN1CWim046CVjS18iuMV2lsb5PbP4ymX\nfs+nMjFBPwnod9tkbUliDBoB2iZbKPKON72epcVlWlvboEo42RzoPkGiGXMELUuwvrhJEKaJTYiI\nEzrdHpYS9IZDspk8m6s18qU5OgbMxjLST9heX6M3SDN23R3Um0uIxhq+UBTLhwjUNvvH5rn09Cmk\nqykUqmzU6qSzeUzSJKh3WPdClg4fxXMsbnzpCT7+1U8jVZbVxWUGPZ+kV8fEx4lbm7gzB/Eyis7G\nU3SXs2QOH+UVN93Bvrlr+dBH/hu+06enJO2hQBhNYXaM2kIdiaR0aIpMIUdrvYaXrxA02vibW9i5\nNMlwSN0fkivYpNMWVjrLwanjLD70bfQgIRgOSE2UcfMZgvYWdiFLkCRkPA9hOwxqTWD0V3RBd0jY\n84n6XbCdnR2MGHSPxz7zFRwlyV17kEb9FMq2KV87Rf1MjfbqJm7aot3YwNYOYjoDbRtkgBkmFAol\nBtEWqaL9gmfti0Ip2AiMgbWtAfumc5y45jgPPv40UTchimO0DhBKEQ8ihBAj0TIGJRweue8RtE4Q\nQuCkUwx6fbSR1Fcv8dE/+8vL1ruUSNviHT/365iCjVWYIIhGIcuxCQijiJn0BBAQhIaF7ikspfj9\nX/9dpg9dg8IwMT/Hv/vA//kPeDOXkQLIcfm/GiJGR6xHJsQgXiRtVfiTz3wMIQTfuPdR2q0BrtDY\neY/2dp1ER1hpF2sQ0m/5xLEmDg1Ig20rPFuRDPpE+SL9ZpOM55BIgVtwibptBkNDr9uCMCabLeB5\nWdrb64SpNOOVPFsro0AgHVroIMZEmmS4gbCLVETAt9fXiRPwtzdwxzMY20XR5VLbkM2myE3kqS2s\nksm4SAE/8p538/G/+hC5uQqDrTaZSgVpSRq1NpX5acKtFdx0GuVl8BdOMV4eY71vGMu4VMdSLFyA\nlXNnSGKfaBAQ9xMynsvRG29k7dxZCsUC1x+9hqfv+jL3Te/jtutOMFHJkugNLMehVLQZWA697YtM\nTh5gdXkBxqvMTLwct5qwcPEsb37prxEDzyyu4EgLVynK0zMEx47R2nqG/a+4Acux6CwNseItokST\nEwatY9xyniAQ6G6LzMQkxrYpjs8wqPUQhZhOs0Npdpag10RmMqODUEaj0OgYYhJyhRTGTxEPQ0Aj\nlIORDplCHpGzUMIhGvRoNwZ44wXinE18aQOnmCWOY2r1bVKOIIliksQe7WJ4KQrHr6UdniZa2SAK\nY2rtBuASWN4LnrX/n80HIcScEOIbQohTQoinhRD/aif9/UKIVSHEYzvXW/6+uiJAGEO3GxFGCcIY\nbrvxOsozeYQlkUqhpBp5hfXo5IHAoJRC2qPAn1hDPAwojZdHIc+MtmeIDXECOjToMOGrdz9OAqws\nnOLR0w8zwKfTCtGMApA0Me2gz++//2+IjeE//Or7+fXf/nk0Bm1e+Jn0nVFixAgGXD7nYHPZhIj5\n5f/2W3z5kS9z3133c+nsRbq+ZmK2Sm8wIAgMShpmDkxjen16m1tgWwRRgpPJgpJYVhqDS+zHeJYh\n7bmjrSk/QYWaYb9NWN9ExZIwjFnZ7qFERCpVIJ92WVxtEvstrFSKyUqZxsom49UCKTdPu77JU33D\n6sJp7GFAIeWQszxMbIHoM1F2sbMpGottpNLEoU+v2eSjH/prPM9jsNZEODapsSLptMPsbIV+ENDs\nbhMFMSXbQtDj9DOnyE5VmTk2y4NPXiQQNsbO0qzX6TQDZg9excyNN3Pm5KO0m6tIZeP7IT90y+3M\nTc3y4PlvEcZpmk2wejFWGBINGgTdATIF+/ZV6dUex0/WeORr32V5YZ2vPXoXjXCVqBeirTQ94SFN\nl2jQI73vMMYf0t7sUigntNdWSXTC5vo2rqcwSEgCstVJfKNwnYDOegsnneLSUyexJ/fRa9SwigX2\n7dtH0GqDFhihQNkMmkO2a22iIMKPQUgLqRRhZ4gRmmKhSBJHCMsCLUgVUlz36lcTG4mUhsLUGM5Q\nEWGIooRerc2B4xPEUYDcfgIrTkiiGCvtErZDAj1AebkXPGv///gUYuBfG2OOA7cB/6sQYvekym8b\nY27cub7wgjohINGa2CRoY5D8v9S9ebBlyV3f+cnMs5+737dXvVd7VXdXt3rR1hagAQlCHhsZCI/H\nw2CxxMB4HGBhj8OjMCPwMBHYDmLAZgCjgAF5jBgctgAjgW2QZYMsoZa61Wq1urv2qrfvd7/37Jk5\nf9zSWLYH0xiHQ+Q/N95979x340Rmnsz8fb+fL7zz7V/H0oUOKggQvofnuEgpcNX8AikErW6XIPTw\nAw/le2hdEXcahHFEEIW4/vx3bujg+j7nF3J6QL0RcvZNT/B9f/WdfOAnP8z7/9b3AgaJy6vPf4L1\n5QuYxZA+PT74136WCQmFnf0hb5Hk324hvnz78KUqxJidm9v8/C9/FC3Ba0TELpzc30aXJWmas3Z+\nlWpYYaSDqUcYnRLVm5SmQhjwwohJUoCsGPeGJHnOZHhC2IrRjgHrY9QCncWzNAIXMUvYfeU2yeiU\n6YNNGPWRMqYWuBwe71FfXWZSSJabDsZoPv7PfxWdVYSBg8BydOsm450dTsYFclrg12v0D7ZIxyV5\nlqONQOQFeZbiBh6O6zHY3CUpNNV4xkJUp9m5hL/S5eS4R5FULLVWOfriy7z64AH5ZIQ+HTDe38YV\nLqaqmB0dsPO5FynTBERE1WgwmAxZu3yeO3dvsH3nlK0vvkh6NKG20mJzexOvMsQLHfZ397lzb5OM\nDko7rFw8h0vJv/ro7/Grn/08nc4iy3FEEEfY3ox3vuu/oTjsETQXsLbk9GBMa/0c+W4PYXL8Zky8\nWEMoODw4xsyGDHcHqCgkn+4z6Y9o1DRhq8PCuXXG4ymrl6893ChqKLK5XLkSGKHwYx+MxlpJkSa4\nkYctMzCWMilxPMl0a4f64QG+kjiOpBpMiOox3vICUbuJ47jcP01YeeQc4zuQ9CYIKQm8CONaNp6+\nAsenr7vX/idvH6y1BzAXoFtrJ0KIG8zR7n/4z/rSl3EUJwfHrG+cwQioqHjq0mXuulucHCZkRYGx\nFlOWwFwz7ihF0KiTjqYgJdpKBAbhzBWRqnroeRTQPnOGBbekDYTnnuJDP/XfMacAGKo850tP8K95\n9zfwvd/1Hbxz7zLv/c7v4c+89/v423/zR7h7//WrwuatZP7fQ/7dSsaXfBc+juczHQzBkYxOxyys\nLxOEIdVDr9TguMfpwTHN7gKTZH6eUJYFYexihcKLQuqywHdCwsVljno7BGFAmSckZYjfbhI6iqju\nsbM751fWaxHT0ynpJEUGktkkpUocpnlFksyYHh2RjwM8RzHtpzR9H2MsQyRSQO9kFycM2Ml7rCwv\nEcQNjB4icokVhqAZk01TirxiYaHD5PSUlfXHufuZT+CGTZJkSnnaZzaZEShLkg1RwqF4cIhxXPIi\no91pMD3VRG7A8Wmf+toCwvXo3d9kenjAubOP0mt3+Myv/EMefepp1jeucP/eXaY3RyhraD3yKCc7\nd6jGCecvXWTr9h16xyF4gjNXz3CgZ7zr2p/gF278XS62m5R1h4XFBb5w+3foXD7L4dY+Zpqii4Jh\nbwT+3MBk0ylaBmRVSeQ5+I7LbDyjzPcIooo4btJ/sENQW8RzIg4nx5w/s4qnFE4tokxKLBZHCrQA\nXRVIz8fqChW6FJOcmeOQjodUlcT1PBAZ/+z2PktFji0MbitC+SFyeECZW/xGyGKecLCzBVmBVhav\nEyBDhcgdhrt9smTyunvtf5bqgxDiPPA08JmHb32fEOJlIcQvCCHaf9D1FsAa6rFCVxVlVYGxmGyE\n1RUX186yfn4Rz3HmDrJSgAVXgjEWx1E0F7pIJXHUXGKqpIOUCqscGt0lFs+en+clVAVtwHk4E4mH\nvJ3A/7fw1u//rv8ZB8HjZ76aX/oHv8aff+ad/J0f/nF+8x//+h/yzmjm2oMvFyrNJdSWAZ/49C+R\nVQbXClqLi0R+wGDUw4kkYejjRxFTW0fruQ28OBlgrUNZFAyHI9LcUGQaLwjRucFUE+p+A68scJCI\nMkfnhuFwhBQRK4sefreObPlUJqfIJ2Asa1efwCiB1pb84AjPcynyHkLOycj4gnarQS0IcKMQkVcs\nLy1hspzTo13ai0voysyX1UYz6U8I4wCMZnh0TGkEt176JCvriwRhCWnJG599C24Ysn75OoEUc/OO\nG9I5e4mLFy+iDFjlkmYJG49eYrBzyHBrF/fydYo4Ju1P+LWf//ucHPf4zY//FtuHA7LxlLwoqC90\noCrQ6ZiyNOxu7RDVOiRZxtq5R0lnDnfuHLEY3kAUPkOlOb5xF4+Y4y/eY+/FV1hq11BownZMnhvK\nSjI5mpGnKeQVKinw6g1GJydobXD9gpPNHvn4lOkkoXWmg64qHnnkAp6ToWo+ZVnixh4YTS4sZTJF\nuA6OzKkKjXQllTaM9weYfO5CdRwHGy5T2zgDeYp1JH4QkI/3adc7OMpDWDg8mpEd9Smtmj+LConO\nEhxrKGcJUv0XxLEJIWrArwB/xVo7Bn4GuAQ8xXwl8WO/z3X/oxDiBSHEC4r5IDfWYK1ma3OXrKzY\n2z/FmrlSaWNphYuXF+fkJauxZm6l9tohoRsQGk07ilGOwHEkBovQFY7r4ocSXc35gYN+SgWMih6/\n+sLfpWBMv9riP/Qi/OdsX26EKoCEb3r/d/MjP/ohBvv79PYPSUcThqMTmq0W4+MerchnNu6z3G3w\nzJPXmfSHKMejtBpVC4niOo40aF0xm84Y9o7Rsyn1ukuhHEbHp3jSgjE4vsvk9BBhY6Jai8HOJlYr\ngmYD6bmMjnvYssQXAp2XlFVFXoaEjQVCP6De6RAvt5CRwl9q0motsP3aA4SueOTCZZI0mftK1Tyv\nA2NQtQiEJU9LiiSltXSW0tFoE1DYgp39bWLfx6gSt1tnYbnL2fNt3vTEG0jKjG43wgl84npAfzRC\nOi7BhbNcagredPEs690LDHZ6BE6Nyb0evp0i/AjHkSg3wJgcL17CGo3nuHQWWqxeukjgCWa9Hs0i\n4Hve9TeYnN5mZXmV2rk2mZjx5PX/lk5ngbpXJz0c0Tvq47gKoaG1FOGFTfAV0vcQ/pxtES5EzAYj\nOmtLmMLg+zGVzimzlKKyHGzvgSNw/RiceE4Zb3WxQlFOUhARSs3PKqQxc8ZlPeDZtz+JMSUt36W1\neRchLPFCi2w4InS7ZMZFYyjyAk/5GO2jXGi0fEyRkk4yTK3OlTc/jTD/hXBsQgiX+YTwS9baXwWw\n1h5Za7W11gA/xzxC7j9oX577oPX8KeN7CqkU2mj29o4R+Ggz9z1oq1moN3jy6StUFqwwnLoR/+v7\nf4Cf+sWf40c++AHe+2M/zF/869+JFRKJ5dI73sVH/uXH+D9/+gO8/elVHj2TIVbdOc8og62XZrx8\n72U+9k9/ESjZ1zv/f1/1j9C+3A2ZARptB/yDj3yQbtbCO3MFkWU4FnpHpwRKoYcp8cIih4d9yCyz\nk32ee+6zWCxuLQRtSU5PyfIKnZUYckyWEDZDjDDMRmNcqaiqiqpMqPKcQGimVcZocEKt6dBavIQx\nJX6tgR+EjIc9ltfW6G6sYj2PKi8IogBbpXhxiA5cdoY5tcUldG9MzSlQkY/NSk5OK+rNOgaDlgKk\nBGuI2gFCObi+g801XpWz/fxNbr/wEigHPdFks5LJ6ZRz5zdwHUVaGZ6/8zz7D3Y5mubMjvssryww\nHU3J1YDHLl9k7/4+p+OUbtdlOhoSxSUrZy8wGk7oLjSoPJ8sr9jcO8WRAcYYvKiGIyNa3RahK7j4\n5Js4mR5TO3eWjXOr1No1ls9ucNC/R3QWvvY938pTFy6gfA8xSnGrlDybMZgYTJlTzjIqa5jd3sMW\nksH2mNlJQmkMOA6OD4uLXXSR4nUaTDONrsB1oNY9i1CKfHCKMXN582yWYoSlGM8oNXMFaplz88W7\nSE+RTifkez2UdOZmQCTaVkSexeQVXhighcBzHUgycr9O2OqiXIVnKg77uwTt1uvutX+U6oMAfh64\nYa398S97f/XL/uxbgFf+oM9yHYXFkBlJ4CmazSal1gxGE0bpjGSawcOQl1oQcvbiAkopFtIps8mY\n+3df5WR/i0ZZ0l68gJIgheLr3/4k7caUSg9ZaW9wcb3DO69fm+Nadcqz7/hTiELztd/8lyiZsfn8\nlzQIBbPq9R/M/H7t5//FrzE/U7Ak2SH3J5/jB37qh/jEv36OdqNGf/cGhdEYFALBLCkZDgek/SG2\nqsAV1GsNTBDgeg7jo+P5QdZCG993cJTmdHcbXSi8Ro3pacX0dEA5zZBhSKIFViqScY/e1n1kGHNy\nNET6OXEUYtKEYjoldgX9nT28ztI8qs9aFIayLPFiB/IKaXMG4yk1JO969gmiPCMOfIb5Pe69+hrC\nGIQWWGMRwuH05i6tRoAxgCvQpqC7sIIuLUFlODw6xPE93LjG8GTE0MakY8lS3KTTaJCPKqpKMDRz\nmtGTT7+TKh/y9DNPsri+yi988EM4RrB555DKccAK0mmG5ypEMSZWguO9bbQxnByfUIqCvf1jXnv+\neU7vP0cc+AwGA6Sps72zS6/fZ/+1Uz7/qV9j9pnP8v6/8V6ktLi+w9GDE9x6m9WNNsf3t+ndv8uF\n86vIziUaazXixTZxy0V5FUZYltbXyGcOC2cvcXJ8QicOOHP1cbLRhNHODaRbIY1BCoF0AurdLlZb\nrIYsS8mKEhnEWEoEcwu2cgTWWorxABxBkZecHAyQUs6rbQp0IFm//ibiKCZPZrQW6lTKI92fIbLR\n6+63f5SVwlcB7wHe8e+VH39UCPFFIcTLwNcBf/UP+iDNHJQyGWZ0FpaYJhkrKyt0apIqn9eGtbZo\nY1FCELnOvOSoS2xpoZpLcUs0xwd7KC+gtbTMY1feTFtd4Nlrz2IKzSwrqESMB8T1Dd508RpvfPSr\nKBKDxGd9fY35fl8w7R38QV/7D2xf+Fe/w5fgHYNywPd///vZPYCb97e5s3WX0A3xSoe//P3fii5z\n6jJA5CUVirzSWF1ydDBirdvBWgFW0rm4RJbMKGcJufJobqyj9RgzTaicimajjVOPCeMArzQ4qqTS\nIbV6DUGAzUpGRxOSrEIpf27aSVMQFpICqwvqUYdknBJ5FdPTMcOTAeDgTGe0WjG3dk+wbgBhHVfX\nceXRPyoAACAASURBVIOQLK+QrkJYgXQVRV5xsH1EVZSEcUCVa5affJRwuYlXa6KAJJ9RHOyTTk84\n342YZn12NnfItKW7ENJeaBBHMRfOnWPnxi1Wls6zs7XH9PN7hMKgbUXe7FBWOUhIZlMaPly4+jQb\nS9dQQiAtKJ0ic8P46IhhVvLgsGI8mHLu/Hly1ycKFK1cIYWlSgu+4d3P8N3vew/CWNAam2lGt7d5\n8ImXMYUkHYCOI6rsmMbGZQ5v36MaTxkeHTLVGcW4YDra4/D+a8hRn+75y+zfvM25p99IXPPJM4ey\n1OiqpLW2RD5NUIGHqTRRLcCtxwihSKYlju+zcGUDJRQqUNjCIKUirruIwCNs1/FrIb7nsry8AGLE\nYGsbr+4xTEq8QLJ8toV2otfdb/+TJwVr7SettcJa+4YvLz9aa99jrX3i4ft/5mGV4j/aBBJrBZfO\nN3AcxYXzZylLjbEuhS6w1nLz3iaTaUJSJHPjkxQgDEZoKjM3TmMENtfUag1qjZitvVO2B0fsp6cU\nuWU6SeZUXMDoeRSdoWS90UXhsHzmMlAyMjd57nO/wfwp//o14/9+u/nghKIYAZYz9ceoRx0W/IA4\n9hDCJxln+K0GP/aBX0IaeOyNTxHWQqRn8WyB47mk/T7oMcV4QmupThh61Jo1ao2YR9/2Vi49coV4\noYkdjWA25WhnC5NOKbOKvKwY7OwxG4/xnBClNMO9A/JZgWs1rqOQZGgt58AaR0DpMh6f4rqCMghB\nQlUUTAc9CFyOTcFLdw/4mnd8PcqzDA4PH9KENDot0FjqG0sgoHmmiwXypGSa9dl+9XNcvHie7koL\nIyrKrCB3LIUTsrO3g+/4nH/0It3VS6SpxWm16N0/oD85pX1uhbt7m1y+dolveM+fInB9sJZqb5+j\nmzcRjsWLAoL6BrnrkOs5CCZaXsXrLHNyckTMHH127rEOymjSwx0iT+GZmO3tXYqZJisW+civbPPV\nX/tnCTwfFbXQZYGxBpQl7Y8I6hEoiUhyksxQk4rJSCNKS6fWxKtJ0kHGaDRGl5LTwS6WlK1XXmKs\nhzSX1ohCFy/0qTc7KEqchzkhxSTj3NsuAwJHCfSkYmW1iWo3Ma6HtRVCQGUyjE0waU5pBdJodJHR\n3xsiXRchFGevrrOxtkxlPWT5+g1RXxHeB2EN1gqUmL96yuHxt76BuB4R+iEGiJRiZ/eAcW+GknK+\nTLUWzXwlUWLxvBBHFPNOagzHd4YErQZ/6/2fJTcT0pnm5r0eQ+C1O7f5gff9Fj/0v/8GP/KTH+On\nP/QxPvTRF/j1F1/hN3/7NW7eznmQ9OhXU8Z2gmZKSYn9D7Dtv3+TQvOT/8dPMBjfZmv/JVa6K9zf\n3UFan9koQ0iJCmKiwgGrWGrX+XPf8c20/QbK8XGEJcunlFWDaGEJt9YmbndxgpjKaAZHQ8pUUm8v\noR2F8AI838cKg9QVSkh8FRJHDtOqJPAk1lREcUwxGzJJp4yOh1hdkuUl2gqkmjv6HM+hHCZIaUBU\nuL5DbXWRuN6l3vb4nZuf5HjrEEf5TI+PkELSPbeKHzhMd45xHZdZf4wuSlYubFAOCxYX1ijQuPWI\nbFwhtWa6d0T/9hb1Rsy43+fWpz7Nn/7GNzM6PCBY7nD++uNcvvIIk8mApBTEzZgH9+6RTuYRgY2m\nj3QknbPPIq1FVWMmuw+YJqc4jkdgU84udVk6exGv3aZ9dp1ka8aot81wWpDlJYP+kOl4TDEa0N7o\n8sL9l/jx/+0DTPOc6eEhbtQkajXw4xqUFRLL4e4ObujhGY3balMUKZVVtJc6OLU6k8mMyBFMjx6Q\nT6AyBi8MEVkEZozyIwopEY2YLMnR/hzLZx2H4xfv4jYVVWkoK03uOBQ6IagvI6SDshZdBnhuSDpN\nCVVJGNXxa3XOX3qCPEvRWYHjh1y59ha++9vfhwz+mMmcDRZrLWVlUa5FW0sjbiPW1qk5p9zduoVF\n0mjEzGYZnidBWSor8JWDwEGYCiE0VZFjzRy1ZpRlZ++IPJCUyZDZLOf2q6c88XYYng4ZOg16Qxc7\nzBEPNJITtNGgM5Q5w8s/9GkCITBCoOxcR+FHkr/3g+9CvI75dDoc88//9Wd5z3f+BU73R6SDTU4P\n+ui8wo9dHCtw0zGTNMHxXV7Z2uG5ey+RJAnpNKO1cJ7SHFEUCUvtBdyajxYuaXIf8JgNjugsnkNl\nJ5RSUWvUKRKBFQFB3TDupeApZNjBjEeMjzJcCYe7ewROTF1Iwk7MbFrg+S7KdRGOg+/7KCFIJ1M8\nLSkM2GJG4feQ0qGmC6rDAVZbJqMpjqMQouR4Z4+Np9/M8a2XkVIh3YBUTzje2kI4kr3Nba498xj3\nX3gF15VUhaC1tEySzDjYOyFsxMTdZX7iZ/4hsZC4TAmjLr/3qd/BjxZZ63RISkNgJBpBa3mJJ//E\n2ykqw4u/+wmqrGQ8rTg82KfT7jLLpgRxTKZy0v6Qca8PxYjuuccwwqM/m9JUhiydsLKyTGIipkkf\nJaYg5pgzJwxxw4ilN1zh6OVXcJoBxSjBOw2Imh2moxE6m9BZWiIdZvS3B9TOCpavLnF4Y4tZCRtR\nHUcJ0qKg1m0yyy2yyIlrHjufeQ7Hd2h3lxikhyglqF9cYf+zd3FCD99V9PePsWlBygG+H5CPphD6\nc/FN7DM5yYkX66ik4uXn/g3CWKxRDHY32ZQOv/0vf4Pzj5zntd997XWNx6+MlYKYyzePxxmTIkfY\nkjwrsaXGVSErZ84hHUmVz59+Fosw4iG4VWKFJUegjUFIh7jVpipKLp4Lkdbn2/78dQaZJC8sqtLz\nmVBAXItotTxiTxMpiy9zrGvx3BDhdCmsZWw1U2MYGMtpqTmevP4NhVeLGaVDjnSPN77pWUrZpB6H\nLCy38CMX6pKzVyIuP/IEl68+Ri+bIdyQZDTBlILLZ9d55MIVGnGdlIJ7n3sFRUhaKsJmE4qSwc5N\nktMEaV3G/SEawXRwSDqrMKKi3l5gOjjFKoW3eBZVD1hYP0+VTshnKWkhMEbPJeNK4QaSqOGQZWOs\n45GUFe3FLo2lJeSoB7OE06Mxs7LEijk8zgsdom48pw194SUoDMkopUgmiEoj3QBXhlR5wW5vH+m1\nqK/EWGMZHB+jqwKbF9QbddYvLtDx5gCSLKvx8qdfwkw93vCGayzUO2xu7ZOcHPIn/+y7SZOEV7/w\nPJcuXOXiubNUJuH0aB9HwPLFq3QaHayRjGcFzaUOraU1Vp54hkn/gChsEYUO6XCGshkz2SCZ3CMd\nj5iczJgNRnPFqCtxa4rBnZto5TIepdRWGiivgxIKIeel7NksxypJ0jvg+OZdBrtDHCFZvXiRZuth\nPEFeIISLV1UYbcnGBVVpEEAyGuEIgfIFvZdu4zgK13UxjqB/Z29OIJvOqHSFsA5SKGyl8YSkfmYV\nKyVhzVDlBX5UR5gSbR2O+4eErk/odl73ePyKWClgNZWQRFFEmufk5ZRVMaMqNc1uSHoy5fKl89y9\nv4lJS6TUc9h6WWCoKA3Y0pCkCpuWjE+PKaqU++M9uGmoNyNCBY4SPHa9Th1Yu7DKX/+vn0FVFcp1\n0EZwOh3hUkOnJf1ZRTUtmeUwHE0YDjSjWcYoN0hy5qi2/7imocwyglaLn/jgP+HPfVOPd3/Lt/Hh\nX/5pvCLkpaO7nL94lWloCX1LMSw5s77E/r1beFFENhpy3N9n/3CXuBnRv9XHcyQPvvg8AZJ8NMZp\ntylmI4h9JBWyqMjLAiEcNM5cy+GUuL6iN83xiwGzcYa1fZzAQ0tJzXeYZGK+by4lRaEpeyU6V6yt\nttHGQCAp0ym5lly8cpXNV24DUIkK3w8onRgzHswrF1VJIQR+OGcOGKOx0ym546KEoeO5FGeaJImF\n7QFRGDKdZjQvLWEKwf1X9wnCOqP9TZrTFNex2Czl/p27nLmmsNMeYrGLLyVf/XVvY/ekx63bdxh5\nPn4QMZvlhI0W+w9usrB4lsnuNoHSHO4kEAnyISBdwsAnaDewog/GpZie4PhtymGfcjKj1l5habVL\n7tQ52btFEDRo1gTDLCeZFnhmihe4VJME4Xh4fooIa1TjkiAICeoxhZQYrfnip55HRjUuP/0ku7dv\nc+Gp6xzdP2DcOyItcrw4Qqc5buSiPEmVKXRe4FiJnWV0zq8xeLA7v5ezCX4coa3BFTAZTwk7dVqN\nOkd393FCF53PMBYc65Hc34XCMjz7x2xSkNLBFfPcBuW4WOD533uRS2sNmo1zCCHmIZ5rK/T7A5LZ\nbG5Ano3ZerBDpSROUZAXOfsHpxwenCAlHH3+M/zshz+OAa6vK+K6w+1XXuCJd/xX7Gw/x/v+yvvw\n6wFeq8niQova8iLrG0+w1OrQaNVYPbtGI4p5RNUJvBBP+qAUJTk5JQ4uFh9FjovDvxs1D2EU47iC\nwcEOv/zhf8HapTUeZAmNWcrjGxtY6TKtHCIlGKf7nOzu0V5dYjY5wquH5KMZptIc3z7iyvXHeHXv\nHqbKwQspKk1kHQbTHt5wnjqkpEG4PrqwFFlOVK9RX1xG+SFxu8JNMzxrqJIRtXYXrxGT9sZEtQ5l\nZRDKYrWg3m6j/RKFIM8Tnjp3mRfuv0bghFitaS+3ObjRR7mCstCsLdXYHZwihaIyFj/wyaocjMHY\necSO0CWNxWX2twfEtYR8UmKUQ5JlKCXIj8Yk9PHDBrPBEFcoTOgSBl2CJjzy+FO88NwnuHr+Go4U\nnE6P+dxnPsWTzzzD57/4W/zFv/CX+PGbN7j66DVufvoFzj36OOPhPpkvsXsJ5y88wtHJAaIhWTp3\njpa/RK8mGGzt0+q6CCSDfh8hHdwwwpiEvFrg6WfX+Z29e5RFispKHBXRXdxgOt4lH9WYjBMcmyOt\nx+xg7qZsnT9P2u/jt9qk/QnW8Vl/7Dr3jk+5cv0NyKCOTG+hjcSv1ciTGX4cYq0lmZU4UlDlORur\nTzAZ7NE/POXxt30te/ceMOjtUZZynqcqBGG7RZak+KrEWE0YBCSzAqksDb9B6/oit19+jdHR8ese\nj18RkwJGz4Uc9iF81RqENWzujhnrfeoChFQILM1WkzxPsNaSZTM+8fHfxfdCfJFxb2/I9HRAlSVI\npbh5+x66KqmMRagajgsvv/RJ/iR/jd7hlDsPTud1dLuFUM58WyJ+fb6UFgKkwtoKx3HxpUIoQa0h\nWV5bJe5ept1tE3c6rK11WFltcaZTI24vE4chnUYLhEA6PqsXrnJSjvjMp58jSC2HR4f0xg2q4g7d\nR68hlMTJNWtLK9haDdxjrBR4YR17csjCmbOcJgntjQWGm/uYqsJ1FL2jXcg13SeucHjz7lwCnqd4\ntQjXERSzGTt37lNrt7i8vMxMava3D9FJyqw/pLbUZTg9wq87yBJc4eF6ClVWhOuLTG5vIpTLm/+H\n/56Xf/Bvo5Ug7q5DHHJ6d5uyMJhSc/Jgbw7HfVhazrMUz/eoRIkpK2TkUxWa2tICYbPGwc0bNNeW\nGZ5OsGWBEwa4oc+1t76F25/4JEKAF7uM79/BEZLlMwt8/OOfZGWxy6ysyIuC5z79CtU04NbdfZ55\ny7v4Rx/+J9RbXRKjieoxB9sPCOtNzrRqnKQDNu/dptZoEgcBj19e52RsMNv7VNmMrTtj4vXWnN3t\ne2gF4+MeZ9dXee6j/w+uOg9YpBvRrLsYVYL1qaqcequOtE0ym+NkFa12iM0L/CBAl5Kw0cBpewyO\n9nn2mbdyPBjSDASZ62OL0dzy7weUWtNZXaLY2SfPNNJx6B3dQyczLlx/hL3BHomZYayl1lakqUOR\nVRhjaXRa5NkMCcymKbg+6BLKijuvbVJUmiuXNniZz76u4fgVMSlIx8Vqi3JcoKIyICoHqzVH+6cc\nYbgex1g7T4ySYi5HLvOCwA+o1X2Gx9OHTDpBZUBZS/90SJ5m88Ep5pj4skgpAcdzkUL+f5JpbTXC\nGKwFrQqskPM6tetTVRmZllgFk0RxeLQJzsFDf3yBCiKUEgjp4noKGcS890d/guODE1bX13j5E88T\nrHhIozk97CEFJIMhOIp0f0C03OakN0afzHDXVli/dJWTB3fxug2iaZ1uw+XkZETVbCFKQ1GWqFAj\nq5xwaRFlUuJWnWQyRZsSowWFTrFORKg0gas47E2YVJogjknLAiMUe6/dweu2GR0dEQcdcMDzQwai\nojGdceb8Ofa39/jZv/nDPPMN38KLH/sQ73zrm/m5v/djpLMpILDCUpQGP44Yj6c42uK4LmWao/U8\nEDibpKxcukihx3hjwer582TTKTqZ4sUR9aZDtLLKyfEm6XSK1pa4FlHpitbqEqlaol3bpeH4LEYh\nVaPFk2+9zisvbbN18y5uLSbTLqt1w+defIkL1x9j2BthS8vR3il+o8vC8jmmg2OMknzjd3wnP/SX\n30er20WsbJAOTqjJDr28h1tp4pUuyemUVz73CnG9xaU3X2Dn1i2cWp1ZMkHlY8JGl9HxIWEckJaa\n1soK0oCRHvUln2QWUk77NFZXeGRlnXu9jKya4VUVr33yBdKTQ6yxrL7xcfZeuYtjNf3tPYSV6MoS\n1j3KSUbc6VJaF9fNMNrFCEFWGLAWz/cQrqDKC0zpkBcGISzd9RobF5/k9GSX8MiS5ym3b7x+te5X\nxEGjtRYhYTqeUJYlttKURYaWUJUlVIYv3LrPYJogLUgsQlg8J2BlY/FhGGc5JziZClcJFFBV84NH\ngUApSWUMRTmXTc9dkRqjK7QtwWg0FissxiqskRgDpsgo0pKqzDBlSZUXFGk6j7dsLyG7KxjXIzOC\nNJ2QTmekkxmLVcWsd0IQheTTEYe3Nhnu9vBrISpqg8lxHYErLGVWkpeaqFNnsRuhbQXNiN7mLqdH\nQ7544wZ+qJjs7FGVmiDy0MoHGVDNEg63TkkmU/ywThj52Iesifz4gEJLjBtTOZamNMQLTZavXqHe\nXMRaiShBBiGOkkgpKYsM5QpC4XHv9j2kEHzX9/wvfOGzv03UWOZDH/0o9UuruGEH4bhIKVHOXMug\nlIN052nJBoHr+yAEfuBgyelvHrO/tQO+wNZjsIqLX/0s7uJZmvUOg/tHOEKhpMNsNkYpga4g3b/P\n0sIyx2EJtRq6LJhauProIktXrzE6Pmb35qu8+uodlPVoLnbYuHqRoqqIljawpWGUjYh9iyNDfuq3\nf4ypTkiSEldVXDp/FZ3MaNTrSEcQhw3cxSa+5+M6ls2XX57nNBQz4nqN1voKSb+HH9VprS0QRnUG\nB3u4sYfjOTRX1vB9QVxvENfaUE1otpqYfELc9jBVxsIjT3HlbW/j5M49HF3hBj7CcTFY/Nib95u8\nYDqY0u+dMBpMWFlqI5J5SmlVlCAEcRDgWJe8P0YpiRc6OIVhY73B6GREURacu3aN2Wz6usfjV86k\nICButojCmDiKUSokCgI81wOpcI1gME75zGu3yL8kVpIWR47Z39wjLy26mKGNxhqDFYAxdM6u0dnY\nwA0cdGkwpiIFhFDE7SbGakypMVqD0SDEvKT5UCQilDOPBRcKo+3877TGVPNrjAXcAOEFFFlGVVVo\nXfILP/MBHN9lOppy7YnHqLcCqiTF91ykKnDcAAfDeDhAaB805KZktHfE6ckJrThg+ewq7aVFLj79\nJjz5sBSlBEk6QjgaN5qbYaSeU4ErSqzyqCqNinzChQY6T9HjlOlUQiMiiGLc2CXLDmieWcRRlnIw\noqzmiHFTGsrDCcOpoZyz93nuU/83b3/iad78putM732B/c98genghM7qBaZakc1yqjzF8xXSUejK\n4DhgjEEJSWklohIEK2eQjTpbN24RRTFVpTm4dxehE053dpiN5xwArEUJn2atzSSfkeSWB3c3WXZC\n+kd7TCvL0Z17nBQWMzni2puvE8Qdlq5e4Mz16+xvT7n1+VexuqJZayKBR9bWWLrwGK6o2P9UTtkf\ncma9yfEgZfdgG9mMcOOYbJaRjo/AD5iu1Ek8hQpCTJ6QDcbobMbJ/QMwhiybMDyZkVQaT2ksitbG\nCqfHfVACIQ17d+7jBQG5yajEIq+8/DKV1Vx45lGWz21grKAyFVZC4Dk4gYvT9KnSKdZYtChJDk8w\nJufkZITVFtcYglo813mMp4yTMVVVYQUEscs0Edx4cIB0AxzlMJpVeH/cougdOacee55kZWGZlXab\njbOrRKFPs9GkWY9pddt0F7oU45TXXtmfQ1mspneoiMO5AUq6LliDEF+iKBtmgwHogiIryPIKI+b8\nZKM0ypEo159H1WMR2mKrYg69MOYhbYn5z5h5wK2SGCGQjjOnIggQzHFwUrmU+dwdd/vGSzQ6dbJ0\nTHflHFK4FEnOJCkpJxlWSlrtDd711e+g3XEpy5TR1hHjcYofePR2egxPe7TOn6NIE6JmjKvUPOqi\nUpBmlGmFdCTETbIkRxQl+XRGp1VDUmErC8rFbwqK7JBZb8DejU3KXh8naBJGLsl0iEAiTIXyJXmR\nEnSWadcqfKWwxnLjtSP+0fO3+dg/+zfM+ilWCOJmm6M7N1g6v4jnunhxTOA5SDOPTisKMY/jkIrA\nk5SRQA+HPPO26wRBg3E+AiHRpyfsvbpFWc6o0oqyKFGRBwIGvVMacZ1sckytu8ygN8WrL3Hri59j\n9crjLDqKy0+9kd2XPksYSco84d3v/jbWlj2CwEVZwd7uTQLf49bmJgfHB8hiTDzLccMG/aMhJk+I\nlGK0v0Wep5RFSWtjATHo0ZoVLNQjXMcipE9BRZlNkFWJrjUJg4jumRUWF1sQLOB1aoz2j6iFK2Sm\norQWVxQINNJqLiwFuHnJ+ScfR+Sa+7e/iDTgRCF+EGKNxXEcJIKlC2eQAmSuCeMa2c6AcnAwJ41Z\njc7nrkfpCPQ0IajFICQLZ9aJJVSF5OmnH6fZVkR+wcbFq697PH5FTAraGJAOrnSp7Jw6oyQIIaiw\nSCXmyGdhEfMX5gm0grxIcQMHXIeF1UVqS82Hp94AEmvkw0Rfi7EWJSRpNsPkGY4QBL6DIyXC9ZFh\njIya4AWgPBq1GMoMTAV2fr3VFQiBFmp+8yrDHME3L5PaSiONpshmPPvMMxxtb7HUiTi3egalFK6j\nSWcJK90Ol/VNsnsvEW2/iqzFiCDisbe+lV/8v/4pG8tnCAKf8ckxlBn9wSaOK6DUCN8niOuouIUT\nhRSzCWVaYS3U2m0m/THJzGLDiPb6KpNJQXo0JO3NaKw22HywS54khDKjffUaQTvCCBdjSnShSQZH\nbN/dRmJAwt//4Ie40vbm5zOuAhz8dozRhri2iBdFLC22mc0yhDffvkg515G0lrosra6gBwluLWTn\nzgFht8Xs5ibShWyqwRgGpwmdlSWM1mxcCLBlwRvf+BTDw31aS6vEkaXW8ulv30W5IUE1Iqkqbr/4\nEnHzMm9649dRFoZf/se/yO2XbpInMyya9kKHyTQl7R3j6YJ+4lAGPg3PY5DOKMsCL/BBOfjdZdae\nuUrvwQ71jXWiqEWSGjIDZZHSObPIbJCQjcdQjGkuLjM62CGMJIEscP2CqFFnNDvFryRes0FlKzzX\n5+j4lJe/cIel9Yt4psXWnRuM94+QSuH4IclRj2qSEioDpeVoZ4TRc65nOhmzsL7GbJxQZAUg0EVB\nVZSYJMPaOeNRWk2qDeMKNpZqbN64QUlM55l3sjscv+7x+BUxKcyrDhZd5ZSVQas5D8EqNc9Tspay\nMlRlSVHZh4lR87g5ae08gNNUnO5vk/VHc2Q8IIUgaIToylAZQVUafM9hNuzjuAVvbfq8fTnmUjOg\nGSoC38WTAjcM8eKYqFXD7a4g6h2EHyAsWAOmLFBCzqmLai7TNtZgjAY550IYKfneH/wBRCWQbYde\nbwaeSz4uiBsNvuar3wpjl/PveDeql/Ked309Jks5v7hCHcm19SvYOCablowGfXxvFcev4YcefuBT\n5hqRpOSTFJNpBNWc4eeGBLWYxsICsYJiPKNKUrxYIWXFsDdCVhJKw3hQUQ77LD1xiaARkJfQWbuM\nLSuEEVgU1hre+z99Oye9E4okwxagtebspceRjuAtF8/w5BOXeeKxx1BSkaXZ3D2tK4JmndB38GKP\nbDaDJMXxNe3VJUTc4Ju//T0od57opZMpk9EAN5L0Zi2kHzCuDLowhA2f8XHCbJCydPVRdFRC2KIw\nFck0ZdTvc2vnJjLqUEw2Cdt1SiPZuHgBqVwaS8sQheR5Si2ChcYZBhauXb1Ic72Lp3w6nSVwS2ZH\nA2almg+ywMUJFHEcovOKqsi49vh1lDS4foP9w128VsTx4SHGbZAOKsxsiiMsIhb4jiGsN7COoBF7\nNJZajFNLbW2Ny9efobNyDmMEF978FiQKKwzjYQ5pgZ1mSCdAmwJrLKODPmHs4QcBWVJQzDJ0qbHW\nQlqBnmJCl0IHXHnTY/STKbt3tnEXatjpjIvd+HWPx6+ISWG+j4eD42N6gwHTbEKlK4b9MYPRiHFa\nkBZTslyjhJgvFSygK1CWUDkEtmJdeJx1JeZhPH2sFFWRUxUJWlcoqfBCyWjQpygK+NPfiqMLrjYc\nvmY15l0bNb7pQpNvPFvnjYseKnSIXEngubhhA6/bweks4i6u4vguwhqkUAilUGIe//Wl8wchFX7Y\nYWFxkXd9zTtAas5fvYapSoo0Z+cjH0YKhXQV1lrufOQj6DQjzxNenG4TdmsIVxEtNHC7Z7DVjGih\ng7AGz1cYBXG3STUeYauCqipRNoM8QYU1TqczdC443NpicnzK5HRMUkZ4SGypqXUjwu4qNddhcGuP\nbJowPN6kv3+TylZoa+ZImLygtz/i3CNXwPep8hRTlBzefZn6uXWkmFcsbr72RSyWWhRgNEghWT+3\nhPKgKDM86TJNE7Y2+5jsiM5qh1RPsYGPEBY8DyUAr8az62cIagF7u/fwFmqsP/ZVnDmzTjKZ8crn\nXiSYxmy98nn+X+rePMj286zv/LzLbzn7Ob333ferK+nqSpZlYcvygmU7QMBgQoYhwewQlgxJRQJu\nigAAIABJREFUUQGTYaiQSc1QZJuhkklggAJCSAYI4BkbbIxtQMLIsixru7rS3btv9+31LH223/q+\n7/zxHnsyqQmlKciUpqu6Tve53advnz7v83ue7/NdagFUWw1Wzq4y2rjDxVPnWTx6P+n+kEoYMyxC\nBltbBAKqWpOOS7Z3R+xtvMT7HnsnN7Z2SJMRo4MelWqAFiHD/REHt3YYbGySDHsIpagc6aAWIpKD\nPtu9O4hazMp9K5x4+DztpRXmThxHaofISyaDnHT7DraA5KBLUFEEArLJlGw6YrFTQaRbDEdjeoM7\noBWrp1Y49dVfh2rMo5VEKa+i1IEibjdQcYBJE0QY+jHWghIOk+WYzBHEEXlqOXHpXmR+B20Cjqwe\nRxIgRUTaf431zbXXfRzfGCtJb7zE4sIclJaK0pQIGs0ak8EBWjnGY4tzPnRTOIGV0ic05gXaltTL\nnO50irM+FwIH0hoqjc7M96OHjhVBILHJCJEl8Nyf4maR4coYSlGQZ7lf6zjBok1wDUEUVhGqyotW\ncmdv4s00hHd+soCTEmFAV0JEnuOkxCG4fXuPBx+8h3SyS6sxx/Xrz1HmhmpY8aBe5ygIS7S8yHRn\nFykUn/3Ex3j5+askVcuKqjC9u00+GVBvtskGQ2ygSZKcWrtFbgp0EJEXltbCAoO9fYrScbjdQSmD\nkQVityArcmSoCBuWTmWRafeAwfYBtU6Dg8mYbJwQRjX2drZQsTe8HW32GBVDorkmygr2rr3E8okV\numt3UVpiioLsoOct9J3jzp09jBJIHLoSYPOS3e6IweYucTWkNJZ6c46lhTpGdqgdbnLlynPMnz5M\nsV2ldI6Dbpe3PnIv58+f4JnXXsVpydET55lXAqqaoyeWufb8NS7ec4QimadarXPogTOUiWXu0gW2\nsgP6t6+QKUlscu7cWacVCcITF0hf+zzD8QEXH3yI7e1dPnv5s8hqRHvhMFuvXaOyfJQsu+v/Hq0m\nZFOCVhuXjSjSNnI8Biqs3Hee3ddeYzqcevn3JEOLgKw7pKgIGgt1Rr0uNUpyqiDrhFpSbTU4GEzp\nHDvKIJmy2IKzF9/G+tot3DTm0LEq3fl5uhtDiklOtdMmmQwhSWaZQgqTWe+dIMDpAEmJKVJqrTmy\nAjZeuoEpcia9Z1jrnkavzlEmlmMX3syZsyUv/t5zr+88/hc65/+v3gQ+QFYKgXQOh0BYQ6ACj5YH\nijQrCCt1pPSIuMSCcN73PktAaLDeC8F9OVVekqaGQS9HCUEl8ghsmg/BWNIbr2Dw2IVz/l1K/38Q\nzmGtQ5aOfJpQjHu89/gRgqpFKY3FIZVCCInCgvJcCyyUWcI9b30HP/p3vpbK3BE+/8fPoBtzVMIm\nwgm6IsJJyfLJRVRZUl+o4pxg8ehRWu17qFU/iNqKmIxyVJ7ROXyE0pSk0wSpYoqiwJiC0fY2VknC\nWJImE1ori5RZwfqrV7l15Q69rSFRLHFWYNMCsgmZkDgtUJWQpfkjjEdTkiShOrfKPfc8SFGUTLt9\ngkii4pBsOmGaTsmzGrU6GO0LXmEkpjBcvXULYx1FURIYR2HBlJZOu8aw2ycINdZ6WXuRJ+zuvkZy\nMOJNpxdY6KzQrtQ4dOEMyWBCs9ni0vmLXD7Iecs954jiDvtrt0myMWlesP7aHebmquw+/TL7n3+O\n9U9+hrtPPsXe5z/LwYtf4Nazz9DfHVBMx7iyZH5hnjiUrLQmCKGxk5Q863H0+DwHmz3SuwW719ZQ\nQZ1IOIpR6rUOkUNUIqx2HPQHgGHu4n00zx8jDBUZilYzpNAhbuLo7e5SOdyhiiQZjqjMLXN3bYdO\np83mjZtIlzHpDxhOhty6tUFWjOiPp8y15rn3gYdY62+inCQ4fAZpQTiDycd+VnXKE+yERWAwMsKU\nfkwVQqKDkDzPmT97GuEEzXaNSqOGGeV0ljs447jy5Ge49urzr/s8viGKgnEOISRCKBxQlAVJnuOM\nZHTQI08zKjpHxgKpwOF8bpxzGARl6cAZnMMfTP4vnCKqKlrzETqUBKHAOUM5yRgWJVfCJi/Fi0zx\nYffSmRl+6V1usG7m3GhnudGCb33TRVQASmuQAqEVTkUIJVFagrC0V07yt37w28jDw1x6+8P80r/8\neYbjEUdO3IMUjl/8778LrGP72T+lULD74i2mWUY62WNq7udbPvB1vPXiD3DxTWfZ3R6wff0atUoF\nGUYoLajGEdVqDVcInxMpNdV6jdJJmktNVCARhWE6GDPuGzAlQb1O/+4+WgqsdRw5fZS1vRssnj6N\n1DFJfwsZxog0R+G1EGEYgnFIa2i2a5RpDW0hywsmvT2MM6xfu4m1liCOMU6QJoZKYFBhiCwNAsfS\nkRZRQ3CwN6IYhwy7e3zkf/skgXOk4x7T4T55kXDuobPcGSS8nIScPH+WibCkhebzf/IS67d7WC1J\nxlP/NxGKqNVEOoOxHgQWKvIiomaTw2fvp1KPiZsLfO73nyJJpxQ25cVnX2M4diwvrVCvCi9drzfZ\nXr+BHBpKY0nykkOn5wmlwxUR2dYeea9LOdkFLTl1/hxORojpGBkKJknOZLdH/6BHVGswXtulYsfs\nrK0TBKBDzfzqUQ6fO41JNlluzUOSs7V5GTfusdqcZzpMya8/iZCKIA4xRUGlHmEtKC2Qgfbr2mKE\nM8ab2ShPsJNac/78CY6dOkfcWMBMutx76iy6yIkqAZVGTLL//6GbsxDi9sxp6XkhxLOz++aEEJ8U\nQlyb3f65js5KCKy1aCWpdRpYJynzEhFBs9MBFRN1ljl15ixRLYCZcNniKK3xMfXW4Ht6v3mQwgdO\nitlXCylQwtCixEwnWGtIspzhoOdXjULNLBXFrDKL2f3+PiHA2RwlHI+davvHtrP8aClBS4QKKA0E\n7UWGRcn+lQ2efOkGjZVjmGnGzWsvoMOYbFLF4aXfgcWjx0JTZILDaoq1FWS2xXNP/ymNVoREU2s2\nMAJG3QEH3QOi+gw70RIsJElBux1gigAbRlRrIVJLpAIRS3QYoWtVpuMJnWNLqLhGkIZM76yxcOQo\nRV7gRIkINSrWvkeVpff9k4qtG9cYj/boHDqFsgJlQRSGPCsoTUmeeNs0JS2rx46yvzdAakl7bpla\ne5EH7r+f1WOLRLVVKmHAtDtkGnQYqyZHV09x/KHzPHryHp4zAVIHrI17nG4tUytKfvTDn+Wv/dVf\nQCA5feYenBMIoTn7+LsIKm2gBGsxOiKoBBxbXcJEU6quZPPWLU6cniMPCnTcINKSa9vXcBFMM8Ox\n03XSIqWqJGniOPbIeVaOLTPpp8hmi8ZSjbgeMu0mNNqLTLoDdvYPmAy6BEKRJjkLyw1ckhMHVaST\n6GYV15wnz0rqNe+NUVEtWq05Vo8eo7u9TW9vE6xmWhZoK1g5tsqwm6ECQdxoIoUkTUqEKUCALS15\nXuKMQqsAZzwTFyVRkeXqSy/TzwzT/ga5azLVUzav3OTutWuMBzuMt1+/veBfVqfw7pnz0ptnn38Y\n+JRz7izwqdnn/9m3Lx08JwO0DkBrnHW4wu//g0CzurxI4BRa+hAY6/yJtFmBdQJU4FsqJ5AzdyVn\nS/JkRJmOUMJ5B15R4Hp7THKDswZT+AwGYQxW4PMlZz+DmZvTl3IabJHhygKSBFc6/CJEIKRAByGq\nUgdjOLj1Ip/57X/HymPvZO/qazzxNefZ7d5BRTHWlry6/pzHH5ylkIqsdCA01bkKn3/pt/j53/3H\nfOTmr3LnVh+11IFalWMnj1CMxwRRjCkLNq9t+pZ8nKG0pJxO6W8dcHAwpBJHGBRaB9SWD7F4/DhZ\nMqbVXiadGqphxMbL1xiMR2T9FGl91yWRmCRnsjOkKC2uNJ5YYxzZtGB/a5f9jSuURY6zFiEFUktG\nByNf1IWiKCx3N7tI5aXuezt30TanVo0J4hrjZIOdG1sE1QZrz/8ZNk3Yzbu02jVyVxD55RJBEVFx\nA5KDCcffJnngzWeZO3GE6tFlLP5nF1Jx9vF3IWcF/LH3vo0f/oc/y9/9oR/lwpGzbG9sU6vF5LaB\nHmYUVtNsrRAMBbtrOySTfXbWc1yScNAdkKcZe9evIeI603GKLMZUGjHTaUqZTTGDEXtbW8RNSff2\nro8iCCGzGVFDsXTmKEWa4JIcO80pkpTe9g6BjmgfXUJNU5wNyIKAYtpj+9ZtXDagnHRZv34NoUPm\nD3cYdbuYGTZmEEjhwWEdSDAOJwQiCMjLAlVRnH/Lu5k7fZo3P3I/Zx5/P83OIteffhodRlSDgPbC\nMcry9R/m/1LjwweAX5l9/CvA1/95X2ytj0eTQmIKS00rgkABFiF8ko7Gg1sOh3MWax0456slXhMh\nACPdl23grXOM9wYc7O7hrCUMvOip7PcpbMFgax+XJz5gRkiEczgMOIHBFyv/7q/KTipsniNUiFAC\nHarZtkEQxzWq7/tmhBQIqcimJQeD62gMb/vq/w5Ky8FwRLxwiF/9939I87F3+HHJKErnqN7/EOcv\nPIwNDdf+5BcR+9scObNIPhwxTkE4TT5NcJFm5Z4TlGmJcx5XQUW+iDqBmxSMurtYK3FRhLLe5MSl\nGZPeFgebu2y8cofJwZhIarJpTrVWx1hLqBRhq0FpDJUoJssMpsADZbUqAQFaBSitKZ1DCMHx86f9\ni9Q6hmmK0Jo8z7GlQQnJ2594N4Ot27zw/DXIC+zIYUtHoEEVAik1tVLQ3RrxwtYWD4cGaSxLrZDP\nPv0yo3HC46tw8V1AtU5cWqQ1yCjm03/4MXQtwiGxSP6Hf/DTvPP9D+AW97hxa52wXsU6RzPUuHCB\nWlylvTSHKMak1lFrH2Jpvo0tJ9SqCpuP0bpJkk0pxwXDO10GGwMoJc2jc/TWd7HDgoMrl6k15xiv\nDxhtXKdz+BBU55A6oHm0g1IWdEDr6FFQGmHGrN18kbXbVyliOL64QDYoSYa+K6wuHWHQHeLKgr21\nPkoqVBhi8hxXGlSgCasRKohASFSkENq7n7dPnMAqSxhFXH/tFfJsi4ISXW8gpWYynbJ78xZx/Pqj\nC/4ytg8O+AMhhAN+zjn388Dyf+TNuA0s/6ffJIT4XuB7AZSWWAdFnhHUY4wDYS1RqMiLkqX5OZww\nviCUxmMQTnhugzOk2h/OLA4pnMNNpn5VGIXE9SpO+JAYZ0pyBN08o6K8d78KAtJIUdOC3EocAaY0\nPnodT3YyQhI4B5UaThhkGCClF08pKRAq5IG3fj3nHjrEz/07DdUmMphD7ibkbcNTn/q3NOZb6FhS\nZAc0Oi0+8tFP8L7zRxjc+AJ02rxw9w5hb4h2lu2DHeaO1RhZxeKZs5yMY9AhYa1J3usyEWBtgZQg\ngpAynWKFxZgc1YiQpaZ+eIXh7Q1cpYmWmtxk9PenKBwmz9GVkN0bW8S1COEmxNWIzEbY6YSwGmK1\nwhWek58XObaYoKox0+EQh0IiKErHnbVt7jl9DKEVojB0FtsMez5eL2jWaTcDjp19iFazypUrN1E6\nQAWg45h0mnByXkFrnlaq2d/pct/iKm82U5794qfJkxInc37sJ/4V/eFtLi4f5dVn/4xqnnP/V76T\ndn/K1avXCMIaRZnyt3/0e3jr/Q/wR099gczlNDp18kmX9bXbvO2Jr+LyMy+Q5iNqlQZiOmQ6OMAG\nEkrHMM0xxpJMc7QLcbUIO7GAhUqVYlQgQ02Z5UzDKiLLmeYgTIXulZscve8e0jRluNHn0H2X6G9u\nUl+ok3eb6KDKzrVXCY92iJRj4koyk8F4Sm9jExNM6egOe40WhjHToe8MFH4sLXJPZ28vNnCtVZaX\n5hn39kkHI0a9ghvlGvc8eIGdjU3KmwWxChjv30XqClI4zLRkaNLXfaD/MorC251zm0KIJeCTQoj/\nW1a7c87NCgb/yf0/D/w8QBQFDifoH4xo1DSTJMWYgnECZRiwubNL4UqOHTkKeI6CkBIjPLDYWW1j\nnMHFBXmesdudgrPErYj8Zuo7CFtDCkXUaEOsCGjjipLSGKJDpzl87wppqcB5ZNeVDis8iCm1oswE\n7YtvYfL8S8jhAU4olPTRdDaOufcdDzJfMV5Q02lSaxyhGkGv3+XTf9jHpVOEkFS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FAAAg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tLba2tkm6oOtrZju7rE42HL/xUVJome4ecnj9iEk5ZjyaoIKXCpeM1oauDVBook/YQj3JpFBW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\nTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f727415de48>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cls2col = {\n",
    "    0: [0, 0, 0],\n",
    "    1: [0, 184, 217],\n",
    "    2: [0, 255, 0]\n",
    "}\n",
    "\n",
    "def pred2human(img_pred):\n",
    "    img_pred = np.argmax(img_pred, axis=2)\n",
    "    img_pred = img_pred.astype(np.uint8)\n",
    "    h, w = img_pred.shape[:2]\n",
    "    result = np.zeros((h, w, 3), dtype=np.uint8)\n",
    "    for k, v in cls2col.items():\n",
    "        result[img_pred == k] = v\n",
    "    return result\n",
    "\n",
    "def get_acc(true, pred):\n",
    "    total_count = np.prod(true.shape[:-1])\n",
    "    total_count -= np.sum(true[:, :, :, -1] == 1)\n",
    "    correct_count = np.sum(np.argmax(true, axis=3) == np.argmax(pred, axis=3))\n",
    "    return correct_count / total_count\n",
    "\n",
    "for x, y in val_batch_generator.get_batch():\n",
    "    pred = model.predict(x)\n",
    "    human = pred2human(pred[0, :, :, :])\n",
    "    print('Acc: %.3f' % get_acc(y, pred))\n",
    "    img = x[0, :, :, :]\n",
    "    plt.imshow(human)\n",
    "    plt.show()\n",
    "    plt.imshow(img.astype(np.uint8))\n",
    "    plt.show()\n",
    "    break"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
